Electric machine diagnostics and monitoring is commonly performed to identify current health and performance status of an electric machine. Traditional machine health monitoring systems perform diagnostics on a local diagnostic unit. The local diagnostic unit comprises a local computational unit which receives sensor data, performs at least one local diagnostic test on the sensor data, and outputs the machine status indicator. The outputs of these systems can be sent to a customer network, or to remote experts. If machine operational data is available, the remote experts are able to determine the severity of any faults indicated and report back to a customer. This requires the experts to design the machine diagnostic algorithms, and also expert personnel to fill the remote service agreement.
In other traditional machine health monitoring systems, data acquisition is performed locally and the data is sent to a remote diagnostic unit where the health status can be determined by a machine expert. The machine expert has access to all the information about the machine. However, challenges occur when transmitting high bandwidth data to a remote server. Unfortunately, data fidelity may be lost during transmission.